The use of a Roving Creel Survey to monitor exploited coastal fish species in the Goukamma Marine Ptrotected Area, South Africa
- Authors: Van Zyl, Carika Sylvia
- Date: 2011
- Subjects: Fishing surveys , Fishery management -- South Africa , Fish populations -- South Africa
- Language: English
- Type: Thesis , Masters , MTech
- Identifier: vital:10748 , http://hdl.handle.net/10948/1348 , Fishing surveys , Fishery management -- South Africa , Fish populations -- South Africa
- Description: A fishery-dependant monitoring method of the recreational shore-based fishery was undertaken in the Goukamma Marine Protected Area (MPA) on the south coast of South Africa for a period of 17 months. The method used was a roving creel survey (RCS), with dates, times and starting locations chosen by stratified random sampling. The MPA was divided into two sections, Buffalo Bay and Groenvlei, and all anglers encountered were interviewed. Catch and effort data were collected and catch per unit effort (CPUE) was calculated from this. The spatial distribution of anglers was also mapped. A generalized linear model (GLM) was fitted to the effort data to determine the effects of month and day type on the variability of effort in each section. Fitted values showed that effort was significantly higher on weekends than on week days, in both sections. A total average of 3662 anglers fishing 21 428 hours annually is estimated within the reserve with a mean trip length of 5.85 hours. Angler numbers were higher per unit coastline length in Buffalo Bay than Groenvlei, but fishing effort (angler hours) was higher in Groenvlei. Density distributions showed that anglers were clumped in easily accessible areas and that they favored rocky areas and mixed shores over sandy shores. Catch documented between October 2008 and December 2009 included a total of 361 fish, of 27 species from 12 families. Sparidae had the highest contribution (12 species). A Shannon-Weiner diversity index showed that diversity was higher in Buffalo Bay (0.81) than Groenvlei (0.57). Catch composition of retained fish (336 individuals) showed that the six numerically most important species were blacktail (Diplodus sargus capensis) (66 percent of catch), followed by galjoen (Dichistius capensis) at 11 percent, Cape stumpnose (Rhabdosargus holubi), belman (Umbrina robinsonii) and strepie at 3 percent, and elf (Pomatomus saltatrix) at 2 percent. Catch composition of an earlier study in Goukamma (Pradervand and Hiseman 2006) was compared with the present study, as well as data from the De Hoop MPA, which is closed to fishing. A multi-dimensional scaling plot of catch composition showed tight clustering of the De Hoop samples, and high variability among the Goukamma samples. A bray-curtis similarity index and dendrogram of similarity between study sites and study periods showed that there was an 83 percent similarity among De Hoop samples and a 75 percent similarity among Goukamma samples (ignoring the two outliers). The two sites are different with respect to species composition, but this is expected because they are different areas. Differences between time periods in Goukamma (i.e. the previous study versus the present study) were not significant. The most significant result from the catch composition analyses is the high variability among the Goukamma samples. This can be explained by the variable fishing methods used by anglers in Goukamma, compared with the standardized fishing methods used by researchers in De Hoop, and the fact that fish are more abundant and populations are more stable in De Hoop – giving higher sample sizes which reduce the variability in the statistics. Species-specific CPUE was calculated for the six numerically most important species. In both sections, CPUE was highest for blacktail, with an average of 0.133 fish per hour for Groenvlei, and 0.060 fish per hour for Buffalo Bay, over the 12 months. The second highest CPUE values per section were 0.030 for galjoen in Groenvlei and 0.039 for strepie in Buffalo Bay. Remaining CPUE values ranged from 0.014 (belman in Groenvlei) to the lowest value of 0.001 (strepie in Groenvlei). Total estimated CPUE for these six species in the MPA using the estimated effort and catch results amounted to 0.018 fish per hour. An annual estimated 3897 fish were landed in the reserve during 2009. Most fish (n=2481, 64 percent) were caught in the Groenvlei section. Numbers of blacktail were the highest of all species, within both sections (2353 fish). Strepie was the next most common (561 fish), but was caught almost entirely within the Buffalo Bay section (97 percent of individuals), followed by galjoen (548 fish) caught mostly within the Groenvlei section (92 percent of individuals). Size comparisons of the six species between the Goukamma and De Hoop MPAs showed that ranges in size are similar, but there are substantial differences in mean sizes between the two MPAs. Sample sizes of all species from the Goukamma MPA were too small to draw conclusions about stock status, except for blacktail. The Goukamma MPA is a popular fishing destination and angler effort is high. It can be considered a node of exploitation for surf zone fish, for which it provides no protection. Even though the MPA allows shore angling, sustainable fishing practices should be incorporated in management plans if the MPA is expected to protect and conserve its stocks. Of noteworthy concern is the occurrence of illegal night fishing (the public may not enter the reserve between sunrise and sunset) which leads to underestimates of catch and effort (night surveys were not conducted because of safety concerns). It is recommended that more communication should take place between the angling community and the reserve management. Sign boards giving information on species which are under pressure, and why they are under pressure, with a short explanation on their life cycles, is advised. The roving creel survey method was suitable for the study area and delivered statistically rigorous results. I thus recommend that it is continued in the future by management. I make some recommendations for reducing costs of future surveys, as well as for altering the survey design if funds are very limited.
- Full Text:
- Date Issued: 2011
- Authors: Van Zyl, Carika Sylvia
- Date: 2011
- Subjects: Fishing surveys , Fishery management -- South Africa , Fish populations -- South Africa
- Language: English
- Type: Thesis , Masters , MTech
- Identifier: vital:10748 , http://hdl.handle.net/10948/1348 , Fishing surveys , Fishery management -- South Africa , Fish populations -- South Africa
- Description: A fishery-dependant monitoring method of the recreational shore-based fishery was undertaken in the Goukamma Marine Protected Area (MPA) on the south coast of South Africa for a period of 17 months. The method used was a roving creel survey (RCS), with dates, times and starting locations chosen by stratified random sampling. The MPA was divided into two sections, Buffalo Bay and Groenvlei, and all anglers encountered were interviewed. Catch and effort data were collected and catch per unit effort (CPUE) was calculated from this. The spatial distribution of anglers was also mapped. A generalized linear model (GLM) was fitted to the effort data to determine the effects of month and day type on the variability of effort in each section. Fitted values showed that effort was significantly higher on weekends than on week days, in both sections. A total average of 3662 anglers fishing 21 428 hours annually is estimated within the reserve with a mean trip length of 5.85 hours. Angler numbers were higher per unit coastline length in Buffalo Bay than Groenvlei, but fishing effort (angler hours) was higher in Groenvlei. Density distributions showed that anglers were clumped in easily accessible areas and that they favored rocky areas and mixed shores over sandy shores. Catch documented between October 2008 and December 2009 included a total of 361 fish, of 27 species from 12 families. Sparidae had the highest contribution (12 species). A Shannon-Weiner diversity index showed that diversity was higher in Buffalo Bay (0.81) than Groenvlei (0.57). Catch composition of retained fish (336 individuals) showed that the six numerically most important species were blacktail (Diplodus sargus capensis) (66 percent of catch), followed by galjoen (Dichistius capensis) at 11 percent, Cape stumpnose (Rhabdosargus holubi), belman (Umbrina robinsonii) and strepie at 3 percent, and elf (Pomatomus saltatrix) at 2 percent. Catch composition of an earlier study in Goukamma (Pradervand and Hiseman 2006) was compared with the present study, as well as data from the De Hoop MPA, which is closed to fishing. A multi-dimensional scaling plot of catch composition showed tight clustering of the De Hoop samples, and high variability among the Goukamma samples. A bray-curtis similarity index and dendrogram of similarity between study sites and study periods showed that there was an 83 percent similarity among De Hoop samples and a 75 percent similarity among Goukamma samples (ignoring the two outliers). The two sites are different with respect to species composition, but this is expected because they are different areas. Differences between time periods in Goukamma (i.e. the previous study versus the present study) were not significant. The most significant result from the catch composition analyses is the high variability among the Goukamma samples. This can be explained by the variable fishing methods used by anglers in Goukamma, compared with the standardized fishing methods used by researchers in De Hoop, and the fact that fish are more abundant and populations are more stable in De Hoop – giving higher sample sizes which reduce the variability in the statistics. Species-specific CPUE was calculated for the six numerically most important species. In both sections, CPUE was highest for blacktail, with an average of 0.133 fish per hour for Groenvlei, and 0.060 fish per hour for Buffalo Bay, over the 12 months. The second highest CPUE values per section were 0.030 for galjoen in Groenvlei and 0.039 for strepie in Buffalo Bay. Remaining CPUE values ranged from 0.014 (belman in Groenvlei) to the lowest value of 0.001 (strepie in Groenvlei). Total estimated CPUE for these six species in the MPA using the estimated effort and catch results amounted to 0.018 fish per hour. An annual estimated 3897 fish were landed in the reserve during 2009. Most fish (n=2481, 64 percent) were caught in the Groenvlei section. Numbers of blacktail were the highest of all species, within both sections (2353 fish). Strepie was the next most common (561 fish), but was caught almost entirely within the Buffalo Bay section (97 percent of individuals), followed by galjoen (548 fish) caught mostly within the Groenvlei section (92 percent of individuals). Size comparisons of the six species between the Goukamma and De Hoop MPAs showed that ranges in size are similar, but there are substantial differences in mean sizes between the two MPAs. Sample sizes of all species from the Goukamma MPA were too small to draw conclusions about stock status, except for blacktail. The Goukamma MPA is a popular fishing destination and angler effort is high. It can be considered a node of exploitation for surf zone fish, for which it provides no protection. Even though the MPA allows shore angling, sustainable fishing practices should be incorporated in management plans if the MPA is expected to protect and conserve its stocks. Of noteworthy concern is the occurrence of illegal night fishing (the public may not enter the reserve between sunrise and sunset) which leads to underestimates of catch and effort (night surveys were not conducted because of safety concerns). It is recommended that more communication should take place between the angling community and the reserve management. Sign boards giving information on species which are under pressure, and why they are under pressure, with a short explanation on their life cycles, is advised. The roving creel survey method was suitable for the study area and delivered statistically rigorous results. I thus recommend that it is continued in the future by management. I make some recommendations for reducing costs of future surveys, as well as for altering the survey design if funds are very limited.
- Full Text:
- Date Issued: 2011
An assessment of inland fisheries in South Africa using fisheries-dependent and fisheries-independent data sources
- Authors: McCafferty, James Ross
- Date: 2012
- Subjects: Fisheries -- South Africa , Fishery management -- South Africa , Fisheries -- Economic aspects -- South Africa , Food security -- South Africa , Poverty -- South Africa , Economic development -- South Africa , Fishing -- South Africa , Fisheries -- Catch effort -- South Africa , Fish stock assessment -- South Africa , Fish populations -- South Africa , Linear models (Statistics)
- Language: English
- Type: Thesis , Masters , MSc
- Identifier: vital:5229 , http://hdl.handle.net/10962/d1005072 , Fisheries -- South Africa , Fishery management -- South Africa , Fisheries -- Economic aspects -- South Africa , Food security -- South Africa , Poverty -- South Africa , Economic development -- South Africa , Fishing -- South Africa , Fisheries -- Catch effort -- South Africa , Fish stock assessment -- South Africa , Fish populations -- South Africa , Linear models (Statistics)
- Description: The role of inland fisheries as contributors to local and national economies in developing African countries is well documented. In South Africa, there is increasing interest in inland fisheries as vehicles for achieving national policy objectives including food security, livelihoods provision, poverty alleviation and economic development but there is surprisingly little literature on the history, current status, and potential of inland fishery resources. This lack of knowledge constrains the development of management strategies for ensuring the biological sustainability of these resources and the economic and social sustainability of the people that are dependent on them. In order to contribute to the knowledge base of inland fisheries in South Africa this thesis: (1) presents an exhaustive review of the available literature on inland fisheries in South Africa; (2) describes the organisation of recreational anglers (the primary users of the resource); (3) compiles recreational angling catch records and scientific gill net survey data, and assesses the applicability of these data for providing estimates of fish abundance (catch-per-unit effort [CPUE]); and finally, (4) determines the potential for models of fish abundance using morphometric, edaphic, and climatic factors. The literature review highlighted the data-poor nature of South African inland fisheries. In particular information on harvest rates was lacking. A lack of knowledge regarding different inland fishery sectors, governance systems, and potential user conflicts was also found. Recreational anglers were identified as the dominant user group and catch data from this sector were identified as potential sources of fish abundance and harvest information. Formal freshwater recreational angling in South Africa is a highly organised, multi-faceted activity which is based primarily on angling for non-native species, particularly common carp Cyprinus carpio and largemouth bass Micropterus salmoides. Bank anglers constituted the largest number of formal participants (5 309 anglers affiliated to formal angling organisations) followed by bass anglers (1 184 anglers affiliated to formal angling organisations). The highly structured nature of organised recreational angling and dominant utilisation of inland fisheries resources by this sector illustrated not only the vested interest of anglers in the management and development of inland fisheries but also the role that anglers may play in future decision-making and monitoring through the dissemination of catch data from organised angling events. Generalised linear models (GLMs) and generalised additive models (GAMs) were used to standardise CPUE estimates from bass- and bank angling catch records, which provided the most suitable data, and to determine environmental variables which most influenced capture probabilities and CPUE. Capture probabilities and CPUE for bass were influenced primarily by altitude and conductivity and multiple regression analysis revealed that predictive models incorporating altitude, conductivity, surface area and capacity explained significant (p<0.05) amounts of variability in CPUE (53%), probability of capture (49%) and probability of limit bag (74%). Bank angling CPUE was influenced by conductivity, surface area and rainfall although an insignificant (p>0.05) amount of variability (63%) was explained by a predictive model incorporating these variables as investigations were constrained by small sample sizes and aggregated catch information. Scientific survey data provided multi-species information and highlighted the high proportion of non-native fish species in Eastern Cape impoundments. Gillnet catches were influenced primarily by species composition and were less subject to fluctuations induced by environmental factors. Overall standardised gillnet CPUE was influenced by surface area, conductivity and age of impoundment. Although the model fit was not significant at the p<0.05 level, 23% of the variability in the data was explained by a predictive model incorporating these variables. The presence of species which could be effectively targeted by gillnets was hypothesised to represent the most important factor influencing catch rates. Investigation of factors influencing CPUE in impoundments dominated by Clarias gariepinus and native cyprinids indicated that warmer, younger impoundments and smaller, colder impoundments produced higher catches of C. gariepinus and native cyprinids respectively. A predictive model for C. gariepinus abundance explained a significant amount of variability (77%) in CPUE although the small sample size of impoundments suggests that predictions from this model may not be robust. CPUE of native cyprinids was influenced primarily by the presence of Labeo umbratus and constrained by small sample size of impoundments and the model did not adequately explain the variability in the data (r² = 0.31, p>0.05). These results indicate that angling catch- and scientific survey data can be useful in providing predictions of fish abundance that are biologically realistic. However, more data over a greater spatial scale would allow for more robust predictions of catch rates. This could be achieved through increased monitoring of existing resource users, the creation of a centralised database for catch records from angling competitions, and increased scientific surveys of South African impoundments conducted by a dedicated governmental function.
- Full Text:
- Date Issued: 2012
- Authors: McCafferty, James Ross
- Date: 2012
- Subjects: Fisheries -- South Africa , Fishery management -- South Africa , Fisheries -- Economic aspects -- South Africa , Food security -- South Africa , Poverty -- South Africa , Economic development -- South Africa , Fishing -- South Africa , Fisheries -- Catch effort -- South Africa , Fish stock assessment -- South Africa , Fish populations -- South Africa , Linear models (Statistics)
- Language: English
- Type: Thesis , Masters , MSc
- Identifier: vital:5229 , http://hdl.handle.net/10962/d1005072 , Fisheries -- South Africa , Fishery management -- South Africa , Fisheries -- Economic aspects -- South Africa , Food security -- South Africa , Poverty -- South Africa , Economic development -- South Africa , Fishing -- South Africa , Fisheries -- Catch effort -- South Africa , Fish stock assessment -- South Africa , Fish populations -- South Africa , Linear models (Statistics)
- Description: The role of inland fisheries as contributors to local and national economies in developing African countries is well documented. In South Africa, there is increasing interest in inland fisheries as vehicles for achieving national policy objectives including food security, livelihoods provision, poverty alleviation and economic development but there is surprisingly little literature on the history, current status, and potential of inland fishery resources. This lack of knowledge constrains the development of management strategies for ensuring the biological sustainability of these resources and the economic and social sustainability of the people that are dependent on them. In order to contribute to the knowledge base of inland fisheries in South Africa this thesis: (1) presents an exhaustive review of the available literature on inland fisheries in South Africa; (2) describes the organisation of recreational anglers (the primary users of the resource); (3) compiles recreational angling catch records and scientific gill net survey data, and assesses the applicability of these data for providing estimates of fish abundance (catch-per-unit effort [CPUE]); and finally, (4) determines the potential for models of fish abundance using morphometric, edaphic, and climatic factors. The literature review highlighted the data-poor nature of South African inland fisheries. In particular information on harvest rates was lacking. A lack of knowledge regarding different inland fishery sectors, governance systems, and potential user conflicts was also found. Recreational anglers were identified as the dominant user group and catch data from this sector were identified as potential sources of fish abundance and harvest information. Formal freshwater recreational angling in South Africa is a highly organised, multi-faceted activity which is based primarily on angling for non-native species, particularly common carp Cyprinus carpio and largemouth bass Micropterus salmoides. Bank anglers constituted the largest number of formal participants (5 309 anglers affiliated to formal angling organisations) followed by bass anglers (1 184 anglers affiliated to formal angling organisations). The highly structured nature of organised recreational angling and dominant utilisation of inland fisheries resources by this sector illustrated not only the vested interest of anglers in the management and development of inland fisheries but also the role that anglers may play in future decision-making and monitoring through the dissemination of catch data from organised angling events. Generalised linear models (GLMs) and generalised additive models (GAMs) were used to standardise CPUE estimates from bass- and bank angling catch records, which provided the most suitable data, and to determine environmental variables which most influenced capture probabilities and CPUE. Capture probabilities and CPUE for bass were influenced primarily by altitude and conductivity and multiple regression analysis revealed that predictive models incorporating altitude, conductivity, surface area and capacity explained significant (p<0.05) amounts of variability in CPUE (53%), probability of capture (49%) and probability of limit bag (74%). Bank angling CPUE was influenced by conductivity, surface area and rainfall although an insignificant (p>0.05) amount of variability (63%) was explained by a predictive model incorporating these variables as investigations were constrained by small sample sizes and aggregated catch information. Scientific survey data provided multi-species information and highlighted the high proportion of non-native fish species in Eastern Cape impoundments. Gillnet catches were influenced primarily by species composition and were less subject to fluctuations induced by environmental factors. Overall standardised gillnet CPUE was influenced by surface area, conductivity and age of impoundment. Although the model fit was not significant at the p<0.05 level, 23% of the variability in the data was explained by a predictive model incorporating these variables. The presence of species which could be effectively targeted by gillnets was hypothesised to represent the most important factor influencing catch rates. Investigation of factors influencing CPUE in impoundments dominated by Clarias gariepinus and native cyprinids indicated that warmer, younger impoundments and smaller, colder impoundments produced higher catches of C. gariepinus and native cyprinids respectively. A predictive model for C. gariepinus abundance explained a significant amount of variability (77%) in CPUE although the small sample size of impoundments suggests that predictions from this model may not be robust. CPUE of native cyprinids was influenced primarily by the presence of Labeo umbratus and constrained by small sample size of impoundments and the model did not adequately explain the variability in the data (r² = 0.31, p>0.05). These results indicate that angling catch- and scientific survey data can be useful in providing predictions of fish abundance that are biologically realistic. However, more data over a greater spatial scale would allow for more robust predictions of catch rates. This could be achieved through increased monitoring of existing resource users, the creation of a centralised database for catch records from angling competitions, and increased scientific surveys of South African impoundments conducted by a dedicated governmental function.
- Full Text:
- Date Issued: 2012
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